{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Optional Lab: Gradient Descent for Linear Regression\n",
    "\n",
    "<figure>\n",
    "    <center> <img src=\"./images/C1_W1_L4_S1_Lecture_GD.png\"  style=\"width:800px;height:200px;\" ></center>\n",
    "</figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Goals\n",
    "In this lab, you will:\n",
    "- automate the process of optimizing $w$ and $b$ using gradient descent."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Tools\n",
    "In this lab, we will make use of: \n",
    "- NumPy, a popular library for scientific computing\n",
    "- Matplotlib, a popular library for plotting data\n",
    "- plotting routines in the lab_utils.py file in the local directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import math, copy\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('./deeplearning.mplstyle')\n",
    "from lab_utils_uni import plt_house_x, plt_contour_wgrad, plt_divergence, plt_gradients"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<a name=\"toc_40291_2\"></a>\n",
    "# Problem Statement\n",
    "\n",
    "Let's use the same two data points as before - a house with 1000 square feet sold for \\\\$300,000 and a house with 2000 square feet sold for \\\\$500,000.\n",
    "\n",
    "| Size (1000 sqft)     | Price (1000s of dollars) |\n",
    "| ----------------| ------------------------ |\n",
    "| 1               | 300                      |\n",
    "| 2               | 500                      |\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Load our data set\n",
    "x_train = np.array([1.0, 2.0])   #features\n",
    "y_train = np.array([300.0, 500.0])   #target value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<a name=\"toc_40291_2.0.1\"></a>\n",
    "### Compute_Cost\n",
    "This was developed in the last lab. We'll need it again here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "#Function to calculate the cost\n",
    "def compute_cost(x, y, w, b):\n",
    "   \n",
    "    m = x.shape[0] \n",
    "    cost = 0\n",
    "    \n",
    "    for i in range(m):\n",
    "        f_wb = w * x[i] + b\n",
    "        cost = cost + (f_wb - y[i])**2\n",
    "    total_cost = 1 / (2 * m) * cost\n",
    "\n",
    "    return total_cost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<a name=\"toc_40291_2.1\"></a>\n",
    "## Gradient descent summary\n",
    "So far in this course, you have developed a linear model that predicts $f_{w,b}(x^{(i)})$:\n",
    "$$f_{w,b}(x^{(i)}) = wx^{(i)} + b \\tag{1}$$\n",
    "In linear regression, you utilize input training data to fit the parameters $w$,$b$ by minimizing a measure of the error between our predictions $f_{w,b}(x^{(i)})$ and the actual data $y^{(i)}$. The measure is called the $cost$, $J(w,b)$. In training you measure the cost over all of our training samples $x^{(i)},y^{(i)}$\n",
    "$$J(w,b) = \\frac{1}{2m} \\sum\\limits_{i = 0}^{m-1} (f_{w,b}(x^{(i)}) - y^{(i)})^2\\tag{2}$$ "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "\n",
    "In lecture, *gradient descent* was described as:\n",
    "\n",
    "$$\\begin{align*} \\text{repeat}&\\text{ until convergence:} \\; \\lbrace \\newline\n",
    "\\;  w &= w -  \\alpha \\frac{\\partial J(w,b)}{\\partial w} \\tag{3}  \\; \\newline \n",
    " b &= b -  \\alpha \\frac{\\partial J(w,b)}{\\partial b}  \\newline \\rbrace\n",
    "\\end{align*}$$\n",
    "where, parameters $w$, $b$ are updated simultaneously.  \n",
    "The gradient is defined as:\n",
    "$$\n",
    "\\begin{align}\n",
    "\\frac{\\partial J(w,b)}{\\partial w}  &= \\frac{1}{m} \\sum\\limits_{i = 0}^{m-1} (f_{w,b}(x^{(i)}) - y^{(i)})x^{(i)} \\tag{4}\\\\\n",
    "  \\frac{\\partial J(w,b)}{\\partial b}  &= \\frac{1}{m} \\sum\\limits_{i = 0}^{m-1} (f_{w,b}(x^{(i)}) - y^{(i)}) \\tag{5}\\\\\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "Here *simultaniously* means that you calculate the partial derivatives for all the parameters before updating any of the parameters."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<a name=\"toc_40291_2.2\"></a>\n",
    "## Implement Gradient Descent\n",
    "You will implement gradient descent algorithm for one feature. You will need three functions. \n",
    "- `compute_gradient` implementing equation (4) and (5) above\n",
    "- `compute_cost` implementing equation (2) above (code from previous lab)\n",
    "- `gradient_descent`, utilizing compute_gradient and compute_cost\n",
    "\n",
    "Conventions:\n",
    "- The naming of python variables containing partial derivatives follows this pattern,$\\frac{\\partial J(w,b)}{\\partial b}$  will be `dj_db`.\n",
    "- w.r.t is With Respect To, as in partial derivative of $J(wb)$ With Respect To $b$.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<a name=\"toc_40291_2.3\"></a>\n",
    "### compute_gradient\n",
    "<a name='ex-01'></a>\n",
    "`compute_gradient`  implements (4) and (5) above and returns $\\frac{\\partial J(w,b)}{\\partial w}$,$\\frac{\\partial J(w,b)}{\\partial b}$. The embedded comments describe the operations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def compute_gradient(x, y, w, b): \n",
    "    \"\"\"\n",
    "    Computes the gradient for linear regression \n",
    "    Args:\n",
    "      x (ndarray (m,)): Data, m examples \n",
    "      y (ndarray (m,)): target values\n",
    "      w,b (scalar)    : model parameters  \n",
    "    Returns\n",
    "      dj_dw (scalar): The gradient of the cost w.r.t. the parameters w\n",
    "      dj_db (scalar): The gradient of the cost w.r.t. the parameter b     \n",
    "     \"\"\"\n",
    "    \n",
    "    # Number of training examples\n",
    "    m = x.shape[0]    \n",
    "    dj_dw = 0\n",
    "    dj_db = 0\n",
    "    \n",
    "    for i in range(m):  \n",
    "        f_wb = w * x[i] + b \n",
    "        dj_dw_i = (f_wb - y[i]) * x[i] \n",
    "        dj_db_i = f_wb - y[i] \n",
    "        dj_db += dj_db_i\n",
    "        dj_dw += dj_dw_i \n",
    "    dj_dw = dj_dw / m \n",
    "    dj_db = dj_db / m \n",
    "        \n",
    "    return dj_dw, dj_db"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<br/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<img align=\"left\" src=\"./images/C1_W1_Lab03_lecture_slopes.PNG\"   style=\"width:340px;\" > The lectures described how gradient descent utilizes the partial derivative of the cost with respect to a parameter at a point to update that parameter.   \n",
    "Let's use our `compute_gradient` function to find and plot some partial derivatives of our cost function relative to one of the parameters, $w_0$.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 864x288 with 2 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_gradients(x_train,y_train, compute_cost, compute_gradient)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Above, the left plot shows $\\frac{\\partial J(w,b)}{\\partial w}$ or the slope of the cost curve relative to $w$ at three points. On the right side of the plot, the derivative is positive, while on the left it is negative. Due to the 'bowl shape', the derivatives will always lead gradient descent toward the bottom where the gradient is zero.\n",
    " \n",
    "The left plot has fixed $b=100$. Gradient descent will utilize both $\\frac{\\partial J(w,b)}{\\partial w}$ and $\\frac{\\partial J(w,b)}{\\partial b}$ to update parameters. The 'quiver plot' on the right provides a means of viewing the gradient of both parameters. The arrow sizes reflect the magnitude of the gradient at that point. The direction and slope of the arrow reflects the ratio of $\\frac{\\partial J(w,b)}{\\partial w}$ and $\\frac{\\partial J(w,b)}{\\partial b}$ at that point.\n",
    "Note that the gradient points *away* from the minimum. Review equation (3) above. The scaled gradient is *subtracted* from the current value of $w$ or $b$. This moves the parameter in a direction that will reduce cost."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<a name=\"toc_40291_2.5\"></a>\n",
    "###  Gradient Descent\n",
    "Now that gradients can be computed,  gradient descent, described in equation (3) above can be implemented below in `gradient_descent`. The details of the implementation are described in the comments. Below, you will utilize this function to find optimal values of $w$ and $b$ on the training data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "def gradient_descent(x, y, w_in, b_in, alpha, num_iters, cost_function, gradient_function): \n",
    "    \"\"\"\n",
    "    Performs gradient descent to fit w,b. Updates w,b by taking \n",
    "    num_iters gradient steps with learning rate alpha\n",
    "    \n",
    "    Args:\n",
    "      x (ndarray (m,))  : Data, m examples \n",
    "      y (ndarray (m,))  : target values\n",
    "      w_in,b_in (scalar): initial values of model parameters  \n",
    "      alpha (float):     Learning rate\n",
    "      num_iters (int):   number of iterations to run gradient descent\n",
    "      cost_function:     function to call to produce cost\n",
    "      gradient_function: function to call to produce gradient\n",
    "      \n",
    "    Returns:\n",
    "      w (scalar): Updated value of parameter after running gradient descent\n",
    "      b (scalar): Updated value of parameter after running gradient descent\n",
    "      J_history (List): History of cost values\n",
    "      p_history (list): History of parameters [w,b] \n",
    "      \"\"\"\n",
    "    \n",
    "    w = copy.deepcopy(w_in) # avoid modifying global w_in\n",
    "    # An array to store cost J and w's at each iteration primarily for graphing later\n",
    "    J_history = []\n",
    "    p_history = []\n",
    "    b = b_in\n",
    "    w = w_in\n",
    "    \n",
    "    for i in range(num_iters):\n",
    "        # Calculate the gradient and update the parameters using gradient_function\n",
    "        dj_dw, dj_db = gradient_function(x, y, w , b)     \n",
    "\n",
    "        # Update Parameters using equation (3) above\n",
    "        b = b - alpha * dj_db                            \n",
    "        w = w - alpha * dj_dw                            \n",
    "\n",
    "        # Save cost J at each iteration\n",
    "        if i<100000:      # prevent resource exhaustion \n",
    "            J_history.append( cost_function(x, y, w , b))\n",
    "            p_history.append([w,b])\n",
    "        # Print cost every at intervals 10 times or as many iterations if < 10\n",
    "        if i% math.ceil(num_iters/10) == 0:\n",
    "            print(f\"Iteration {i:4}: Cost {J_history[-1]:0.2e} \",\n",
    "                  f\"dj_dw: {dj_dw: 0.3e}, dj_db: {dj_db: 0.3e}  \",\n",
    "                  f\"w: {w: 0.3e}, b:{b: 0.5e}\")\n",
    " \n",
    "    return w, b, J_history, p_history #return w and J,w history for graphing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration    0: Cost 7.93e+04  dj_dw: -6.500e+02, dj_db: -4.000e+02   w:  6.500e+00, b: 4.00000e+00\n",
      "Iteration 1000: Cost 3.41e+00  dj_dw: -3.712e-01, dj_db:  6.007e-01   w:  1.949e+02, b: 1.08228e+02\n",
      "Iteration 2000: Cost 7.93e-01  dj_dw: -1.789e-01, dj_db:  2.895e-01   w:  1.975e+02, b: 1.03966e+02\n",
      "Iteration 3000: Cost 1.84e-01  dj_dw: -8.625e-02, dj_db:  1.396e-01   w:  1.988e+02, b: 1.01912e+02\n",
      "Iteration 4000: Cost 4.28e-02  dj_dw: -4.158e-02, dj_db:  6.727e-02   w:  1.994e+02, b: 1.00922e+02\n",
      "Iteration 5000: Cost 9.95e-03  dj_dw: -2.004e-02, dj_db:  3.243e-02   w:  1.997e+02, b: 1.00444e+02\n",
      "Iteration 6000: Cost 2.31e-03  dj_dw: -9.660e-03, dj_db:  1.563e-02   w:  1.999e+02, b: 1.00214e+02\n",
      "Iteration 7000: Cost 5.37e-04  dj_dw: -4.657e-03, dj_db:  7.535e-03   w:  1.999e+02, b: 1.00103e+02\n",
      "Iteration 8000: Cost 1.25e-04  dj_dw: -2.245e-03, dj_db:  3.632e-03   w:  2.000e+02, b: 1.00050e+02\n",
      "Iteration 9000: Cost 2.90e-05  dj_dw: -1.082e-03, dj_db:  1.751e-03   w:  2.000e+02, b: 1.00024e+02\n",
      "(w,b) found by gradient descent: (199.9929,100.0116)\n"
     ]
    }
   ],
   "source": [
    "# initialize parameters\n",
    "w_init = 0\n",
    "b_init = 0\n",
    "# some gradient descent settings\n",
    "iterations = 10000\n",
    "tmp_alpha = 1.0e-2\n",
    "# run gradient descent\n",
    "w_final, b_final, J_hist, p_hist = gradient_descent(x_train ,y_train, w_init, b_init, tmp_alpha, \n",
    "                                                    iterations, compute_cost, compute_gradient)\n",
    "print(f\"(w,b) found by gradient descent: ({w_final:8.4f},{b_final:8.4f})\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<img align=\"left\" src=\"./images/C1_W1_Lab03_lecture_learningrate.PNG\"  style=\"width:340px; padding: 15px; \" > \n",
    "Take a moment and note some characteristics of the gradient descent process printed above.  \n",
    "\n",
    "- The cost starts large and rapidly declines as described in the slide from the lecture.\n",
    "- The partial derivatives, `dj_dw`, and `dj_db` also get smaller, rapidly at first and then more slowly. As shown in the diagram from the lecture, as the process nears the 'bottom of the bowl' progress is slower due to the smaller value of the derivative at that point.\n",
    "- progress slows though the learning rate, alpha, remains fixed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Cost versus iterations of gradient descent \n",
    "A plot of cost versus iterations is a useful measure of progress in gradient descent. Cost should always decrease in successful runs. The change in cost is so rapid initially, it is useful to plot the initial decent on a different scale than the final descent. In the plots below, note the scale of cost on the axes and the iteration step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 864x288 with 2 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot cost versus iteration  \n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, constrained_layout=True, figsize=(12,4))\n",
    "ax1.plot(J_hist[:100])\n",
    "ax2.plot(1000 + np.arange(len(J_hist[1000:])), J_hist[1000:])\n",
    "ax1.set_title(\"Cost vs. iteration(start)\");  ax2.set_title(\"Cost vs. iteration (end)\")\n",
    "ax1.set_ylabel('Cost')            ;  ax2.set_ylabel('Cost') \n",
    "ax1.set_xlabel('iteration step')  ;  ax2.set_xlabel('iteration step') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Predictions\n",
    "Now that you have discovered the optimal values for the parameters $w$ and $b$, you can now use the model to predict housing values based on our learned parameters. As expected, the predicted values are nearly the same as the training values for the same housing. Further, the value not in the prediction is in line with the expected value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000 sqft house prediction 300.0 Thousand dollars\n",
      "1200 sqft house prediction 340.0 Thousand dollars\n",
      "2000 sqft house prediction 500.0 Thousand dollars\n"
     ]
    }
   ],
   "source": [
    "print(f\"1000 sqft house prediction {w_final*1.0 + b_final:0.1f} Thousand dollars\")\n",
    "print(f\"1200 sqft house prediction {w_final*1.2 + b_final:0.1f} Thousand dollars\")\n",
    "print(f\"2000 sqft house prediction {w_final*2.0 + b_final:0.1f} Thousand dollars\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<a name=\"toc_40291_2.6\"></a>\n",
    "## Plotting\n",
    "You can show the progress of gradient descent during its execution by plotting the cost over iterations on a contour plot of the cost(w,b). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 864x432 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1, figsize=(12, 6))\n",
    "plt_contour_wgrad(x_train, y_train, p_hist, ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Above, the contour plot shows the $cost(w,b)$ over a range of $w$ and $b$. Cost levels are represented by the rings. Overlayed, using red arrows, is the path of gradient descent. Here are some things to note:\n",
    "- The path makes steady (monotonic) progress toward its goal.\n",
    "- initial steps are much larger than the steps near the goal."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "**Zooming in**, we can see that final steps of gradient descent. Note the distance between steps shrinks as the gradient approaches zero."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 864x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1, figsize=(12, 4))\n",
    "plt_contour_wgrad(x_train, y_train, p_hist, ax, w_range=[180, 220, 0.5], b_range=[80, 120, 0.5],\n",
    "            contours=[1,5,10,20],resolution=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "<a name=\"toc_40291_2.7.1\"></a>\n",
    "### Increased Learning Rate\n",
    "\n",
    "<figure>\n",
    " <img align=\"left\", src=\"./images/C1_W1_Lab03_alpha_too_big.PNG\"   style=\"width:340px;height:240px;\" >\n",
    "</figure>\n",
    "In the lecture, there was a discussion related to the proper value of the learning rate, $\\alpha$ in equation(3). The larger $\\alpha$ is, the faster gradient descent will converge to a solution. But, if it is too large, gradient descent will diverge. Above you have an example of a solution which converges nicely.\n",
    "\n",
    "Let's try increasing the value of  $\\alpha$ and see what happens:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration    0: Cost 2.58e+05  dj_dw: -6.500e+02, dj_db: -4.000e+02   w:  5.200e+02, b: 3.20000e+02\n",
      "Iteration    1: Cost 7.82e+05  dj_dw:  1.130e+03, dj_db:  7.000e+02   w: -3.840e+02, b:-2.40000e+02\n",
      "Iteration    2: Cost 2.37e+06  dj_dw: -1.970e+03, dj_db: -1.216e+03   w:  1.192e+03, b: 7.32800e+02\n",
      "Iteration    3: Cost 7.19e+06  dj_dw:  3.429e+03, dj_db:  2.121e+03   w: -1.551e+03, b:-9.63840e+02\n",
      "Iteration    4: Cost 2.18e+07  dj_dw: -5.974e+03, dj_db: -3.691e+03   w:  3.228e+03, b: 1.98886e+03\n",
      "Iteration    5: Cost 6.62e+07  dj_dw:  1.040e+04, dj_db:  6.431e+03   w: -5.095e+03, b:-3.15579e+03\n",
      "Iteration    6: Cost 2.01e+08  dj_dw: -1.812e+04, dj_db: -1.120e+04   w:  9.402e+03, b: 5.80237e+03\n",
      "Iteration    7: Cost 6.09e+08  dj_dw:  3.156e+04, dj_db:  1.950e+04   w: -1.584e+04, b:-9.80139e+03\n",
      "Iteration    8: Cost 1.85e+09  dj_dw: -5.496e+04, dj_db: -3.397e+04   w:  2.813e+04, b: 1.73730e+04\n",
      "Iteration    9: Cost 5.60e+09  dj_dw:  9.572e+04, dj_db:  5.916e+04   w: -4.845e+04, b:-2.99567e+04\n"
     ]
    }
   ],
   "source": [
    "# initialize parameters\n",
    "w_init = 0\n",
    "b_init = 0\n",
    "# set alpha to a large value\n",
    "iterations = 10\n",
    "tmp_alpha = 8.0e-1\n",
    "# run gradient descent\n",
    "w_final, b_final, J_hist, p_hist = gradient_descent(x_train ,y_train, w_init, b_init, tmp_alpha, \n",
    "                                                    iterations, compute_cost, compute_gradient)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Above, $w$ and $b$ are bouncing back and forth between positive and negative with the absolute value increasing with each iteration. Further, each iteration $\\frac{\\partial J(w,b)}{\\partial w}$ changes sign and cost is increasing rather than decreasing. This is a clear sign that the *learning rate is too large* and the solution is diverging. \n",
    "Let's visualize this with a plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 864x360 with 2 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt_divergence(p_hist, J_hist,x_train, y_train)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Above, the left graph shows $w$'s progression over the first few steps of gradient descent. $w$ oscillates from positive to negative and cost grows rapidly. Gradient Descent is operating on both $w$ and $b$ simultaneously, so one needs the 3-D plot on the right for the complete picture."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "\n",
    "## Congratulations!\n",
    "In this lab you:\n",
    "- delved into the details of gradient descent for a single variable.\n",
    "- developed a routine to compute the gradient\n",
    "- visualized what the gradient is\n",
    "- completed a gradient descent routine\n",
    "- utilized gradient descent to find parameters\n",
    "- examined the impact of sizing the learning rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "dl_toc_settings": {
   "rndtag": "40291"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.10"
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  "toc-autonumbering": false
 },
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}